GARCH Model for Evaluating Volatility Based on the Share Price of Airlines Company During the COVID-19 Outbreak

Abstract

The COVID-19 outbreak has affected economic activities in the worldwide financial market. The instability of financial markets makes investors uncomfortable because there is not enough study to prove the volatility of share price movements. One of the most affected sectors is tourism namely airlines company. Therefore, this study is implemented to analyze the volatility rate for the share price of financial markets based on airlines company. This study uses one sample of companies from Malaysia Stock Exchange for an airline company that was affected by the COVID-19 outbreak. Data were collected from February 2020 until June 2022. The number of daily observations is 545 days. The distribution of return rate data follows non-normal distribution according to Jarque-Bera statistical test. Next, this study performed three types of unit root tests namely ADF, PP, and KPSS. All three statistical tests agreed that the return data achieved stationarity characteristics at the level. The mean equation for this study is using ARMA (2,2). Then, this study uses Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) for modeling volatility. The result shows there is high volatility clustering that exists during the COVID-19 outbreak. The value of AIC, SC, and HQN show the fittest model is TGARCH (1,1). The threshold effect is positive and significant. Therefore, the bad news is likely to be pronounced rather than the good news. Thus, it is important to investors in carefully evaluate their investment strategy to reduce their investment risk. The findings of this study help the government to develop suitable policies in assisting the economic and financial stability